Probabilistic Streamflow Generation Model for Data Sparse Arid Watersheds1

Abstract: The authors present a model that generates streamflow for ephemeral arid streams. The model consists of a stochastic hourly precipitation point process model and a conceptual model that transforms precipitation into flow. It was applied to the Santa Cruz River at the border crossing from Mexico into Southern Arizona. The model was constructed for four different seasons and three categories of inter‐annual variability for the wet seasons of summer and winter. The drainage area is ungauged and precipitation information was inferred from a precipitation gauge downstream. The precipitation gauge record was evaluated against simulated precipitation from a mesoscale numerical weather prediction model, and was found to be the representative of the regional precipitation variability. The flow generation was found to reproduce the variability in the observed record at the daily, seasonal and annual time scales, and it is suitable for use in planning studies for the study site.     

CHAPARRAL CONTROL IN MOSAIC PATTERN INCREASED STREAMFLOW AND MITIGATED NITRATE LOSS IN ARIZONA1

ABSTRACT: In a 16-year paired watershed study in Arizona, a 303-acre chaparral watershed was treated by helicopter in a mosaic pattern (55 percent of watershed) with tebuthiuron herbicide pellets to control the moderately dense, heavy water-using chaparral. The objective was to determine if annual stream discharge could be increased without degrading other resource values. An adjacent untreated chaparral watershed served as the control on which to base the water quantity and quality treatment effects. Annual streamflow was increased by 1.5 to 5 inches over a seven-year evaluation period. The streamflow increase was accompanied by a small but statistically significant increase in nitrate concentration. The relatively small nitrate response was attributed to the mosaic treatment. Nitrate released from the converted areas was diluted by streamflow from untreated areas, thereby reducing nitrate concentrations in streamflow at the watershed outlet.     

Hydrologic Model Framework for Water Resources Planning in the Santa Cruz River,Southern Arizona1

Abstract: The authors develop a model framework that includes a set of hydrologic modules as a water resources management and planning tool for the upper Santa Cruz River near the Mexican border, Southern Arizona. The modules consist of: (1) stochastic generation of hourly precipitation scenarios that maintain the characteristics and variability of a 45‐year hourly precipitation record from a nearby rain gauge; (2) conceptual transformation of generated precipitation into daily streamflow using varied infiltration rates and estimates of the basin antecedent moisture conditions; and (3) surface‐water to ground‐water interaction for four downstream microbasins that accounts for alluvial ground‐water recharge, and ET and pumping losses. To maintain the large inter‐annual variability of streamflow as prevails in Southern Arizona, the model framework is constructed to produce three types of seasonal winter and summer categories of streamflow (i.e., wet, medium, or dry). Long‐term (i.e., 100 years) realizations (ensembles) are generated by the above described model framework that reflects two different regimes of inter annual variability. The first regime is that of the historic streamflow gauge record. The second regime is that of the tree ring reconstructed precipitation, which was derived for the study location. Generated flow ensembles for these two regimes are used to evaluate the risk that the regional four ground‐water microbasins decline below a preset storage threshold under different operational water utilization scenarios.     

Modeling Discharge Rates Using a Coupled Modeled Approach for the Merced River in Yosemite National Park

This study describes the application of the NASA version of the Carnegie‐Ames‐Stanford Approach (CASA) ecosystem model coupled with a surface hydrologic routing scheme previously called the Hydrological Routing Algorithm (HYDRA) to model monthly discharge rates from 2000 to 2007 on the Merced River drainage in Yosemite National Park, California. To assess CASA‐HYDRA's capability to estimate actual water flows in extreme precipitation years, the focus of this study is the 2007 water year, which was very dry, and the 2005 water year, which was a moderately wet year in the historical record. Prior to comparisons to gauge records, CASA‐HYDRA snowmelt algorithms were modified with equations from the U.S. Department of Agriculture Snowmelt‐Runoff Model (SRM), which has been designed to predict daily streamflow in mountain basins where snowmelt is a major runoff factor. Results show that model predictions closely matched monthly flow rates at the Pohono Bridge gauge station (USGS#11266500), with R² = 0.67 and Nash‐Sutcliffe (E) = 0.65. By subdividing the upper Merced River basin into subbasins with high spatial resolution in the gridded modeling approach, we were able to determine which biophysical characteristics in the Sierra differed to the largest degree in extreme low‐flow and high‐flow years. Average elevation and snowpack accumulation were found to be the most important explanatory variables to understand subbasin contributions to monthly discharge rates.     

HYDROLOGIC SIMULATION OF THE LITTLE WASHITA RIVER EXPERIMENTAL WATERSHED USING SWAT1

ABSTRACT: Precipitation and streamflow data from three nested subwatersheds within the Little Washita River Experimental Watershed (LWREW) in southwestern Oklahoma were used to evaluate the capabilities of the Soil and Water Assessment Tool (SWAT) to predict streamflow under varying climatic conditions. Eight years of precipitation and streamflow data were used to calibrate parameters in the model, and 15 years of data were used for model validation. SWAT was calibrated on the smallest and largest sub‐watersheds for a wetter than average period of record. The model was then validated on a third subwatershed for a range in climatic conditions that included dry, average, and wet periods. Calibration of the model involved a multistep approach. A preliminary calibration was conducted to estimate model parameters so that measured versus simulated yearly and monthly runoff were in agreement for the respective calibration periods. Model parameters were then fine tuned based on a visual inspection of daily hydrographs and flow frequency curves. Calibration on a daily basis resulted in higher baseflows and lower peak runoff rates than were obtained in the preliminary calibration. Test results show that once the model was calibrated for wet climatic conditions, it did a good job in predicting streamflow responses over wet, average, and dry climatic conditions selected for model validation. Monthly coefficients of efficiencies were 0.65, 0.86, and 0.45 for the dry, average, and wet validation periods, respectively. Results of this investigation indicate that once calibrated, SWAT is capable of providing adequate simulations for hydrologic investigations related to the impact of climate variations on water resources of the LWREW.     

Baseflow nitrate in relation to stream order and agricultural land use

Management of agricultural nonpoint-source pollution continues to be a challenge because of spatial and temporal variability. Using stream order as an index, we explored the distribution of nitrate concentration and load along the stream network of a large agricultural watershed in Pennsylvania-the East Mahantango Creek Watershed and two of its sub-watersheds. To understand nitrate concentration variation in the stream water contributed from ground water, this study focused on baseflow. Impacts of agricultural land use area on baseflow nitrate in the stream network were investigated. Nitrate concentration showed a general decreasing trend with increasing stream order based on stream order averaged values; however, considerable spatial and temporal variability existed within each snapshot sampling. Nitrate loads increased with stream order in a power function because of the dominant effect of stream flow rate over the nitrate concentration. Within delineated sub-watersheds based on stream orders, positive linear functions were found between agricultural land use area percentage and the baseflow nitrate concentration and between agricultural drainage area and the nitrate load. The slope of the positive linear regression between the baseflow nitrate concentration and percent agricultural land area seems to be a valuable indicator of a watershed's water quality as influenced by agricultural practices, watershed size, and specific physiographic setting. Stream order seems to integrate, to a certain degree, the source and transport aspects of nonpoint-source pollution on a yearly averaged basis and thus might provide a quick estimate of the overall trend in baseflow nitrate concentration and load distribution along complex stream networks in agricultural watersheds.     

TEMPORAL CHANGES IN THE YADKIN RIVER FLOW VERSUS SUSPENDED SEDIMENT CONCENTRATION RELATIONSHIP1

ABSTRACT: Dynamic linear models (DLM) and seasonal trend decomposition (STL) using local regression, or LOESS, were used to analyze the 50‐year time series of suspended sediment concentrations for the Yadkin River, measured at the U.S. Geological Survey station at Yadkin College, North Carolina. A DLM with constant trend, seasonality, and a log₁₀ streamflow regressor provided the best model to predict monthly mean log₁₀ suspended sediment concentrations, based on the forecast log likelihood. Using DLM, there was evidence (odds approximately 69:1) that the log₁₀ streamflow versus log₁₀ suspended sediment concentration relationship has changed, with an approximate 20 percent increase in the log₁₀ streamflow coefficient over the period 1981 to 1996. However, sediment concentrations in the Yadkin River have decreased during the decade of the 1990s, which has been accompanied by a concomitant increase in streamflow variability. Although STL has been shown to be a versatile trend analysis technique, DLM is shown to be more suitable for discovery and inference of structural changes (trends) in the model coefficient describing the relationship between flow and sediment concentration.     

MODELING STREAMFLOW FROM ARTIFICIALLY DRAINED AGRICULTURAL WATERSHEDS IN ILLINOIS1

ABSTRACT: Evaluation of the applicability and validity of hydrologic simulation models for various cropping systems in different hydrogeologic and soil conditions is needed for a range of spatial scales. We calibrated and tested the ADAPT model for simulating streamflow from 552 to 1,985 km² watersheds in central Illinois, where more than 79 percent of the land is used for maize‐soybean production and tile drainage is common. Model calibration was performed with a seven year period (1987 through1993) of measured streamflow from one of the watersheds, and model testing was done using independent weather and measured streamflow data from the two neighboring watersheds for the same seven year period. Simulations of annual streamflow were accurate with a coefficient of determination and Willmott's index of agreement of 0.98 and 0.99, respectively. For simulation of monthly streamflow, Willmott's index of agreement ranged from 0.93 to 0.95. For simulation of daily streamflow, Willmott's index of agreement ranged from 0.84 to 0.85. The daily simulations challenged the temporal and spatial resolution of our measured precipitation data. Discrepancies between simulated and measured data may result from the model's inability to effectively address frozen soils and snowmelt runoff processes and in accurately representing evapotranspiration.     

Hydrologic Calibration and Validation of SWAT in a Snow‐Dominated Rocky Mountain Watershed,Montana, U.S.A.1

Abstract: The Soil and Water Assessment Tool (SWAT) has been applied successfully in temperate environments but little is known about its performance in the snow‐dominated, forested, mountainous watersheds that provide much of the water supply in western North America. To address this knowledge gap, we configured SWAT to simulate the streamflow of Tenderfoot Creek (TCSWAT). Located in central Montana, TCSWAT represents a high‐elevation watershed with ～85% coniferous forest cover where more than 70% of the annual precipitation falls as snow, and runoff comes primarily from spring snowmelt. Model calibration using four years of measured daily streamflow, temperature, and precipitation data resulted in a relative error (RE) of 2% for annual water yield estimates, and mean paired deviations (Dv) of 36 and 31% and Nash‐Sutcliffe (NS) efficiencies of 0.90 and 0.86 for monthly and daily streamflow, respectively. Model validation was conducted using an additional four years of data and the performance was similar to the calibration period, with RE of 4% for annual water yields, Dv of 43% and 32%, and NS efficiencies of 0.90 and 0.76 for monthly and daily streamflow, respectively. An objective, regression‐based model invalidation procedure also indicated that the model was validated for the overall simulation period. Seasonally, SWAT performed well during the spring and early summer snowmelt runoff period, but was a poor predictor of late summer and winter base flow. The calibrated model was most sensitive to snowmelt parameters, followed in decreasing order of influence by the surface runoff lag, ground water, soil, and SCS Curve Number parameter sets. Model sensitivity to the surface runoff lag parameter reflected the influence of frozen soils on runoff processes. Results indicated that SWAT can provide reasonable predictions of annual, monthly, and daily streamflow from forested montane watersheds, but further model refinements could improve representation of snowmelt runoff processes and performance during the base flow period in this environment.     

Effects of Land Use and Sample Location on Nitrate‐Stream Flow Hysteresis Descriptors during Storm Events

The U.S. Geological Survey's New Jersey and Iowa Water Science Centers deployed ultraviolet‐visible spectrophotometric sensors at water‐quality monitoring sites on the Passaic and Pompton Rivers at Two Bridges, New Jersey, on Toms River at Toms River, New Jersey, and on the North Raccoon River near Jefferson, Iowa to continuously measure in‐stream nitrate plus nitrite as nitrogen (NO₃ + NO₂) concentrations in conjunction with continuous stream flow measurements. Statistical analysis of NO₃ + NO₂ vs. stream discharge during storm events found statistically significant links between land use types and sampling site with the normalized area and rotational direction of NO₃ + NO₂‐stream discharge (N‐Q) hysteresis patterns. Statistically significant relations were also found between the normalized area of a hysteresis pattern and several flow parameters as well as the normalized area adjusted for rotational direction and minimum NO₃ + NO₂ concentrations. The mean normalized hysteresis area for forested land use was smaller than that of urban and agricultural land uses. The hysteresis rotational direction of the agricultural land use was opposite of that of the urban and undeveloped land uses. An r² of 0.81 for the relation between the minimum normalized NO₃ + NO₂ concentration during a storm vs. the normalized NO₃ + NO₂ concentration at peak flow suggested that dilution was the dominant process controlling NO₃ + NO₂ concentrations over the course of most storm events.     

Modeling Variability and Trends in Pesticide Concentrations in Streams1

Abstract: A parametric regression model was developed for assessing the variability and long‐term trends in pesticide concentrations in streams. The dependent variable is the logarithm of pesticide concentration and the explanatory variables are a seasonal wave, which represents the seasonal variability of concentration in response to seasonal application rates; a streamflow anomaly, which is the deviation of concurrent daily streamflow from average conditions for the previous 30 days; and a trend, which represents long‐term (inter‐annual) changes in concentration. Application of the model to selected herbicides and insecticides in four diverse streams indicated the model is robust with respect to pesticide type, stream location, and the degree of censoring (proportion of nondetections). An automatic model fitting and selection procedure for the seasonal wave and trend components was found to perform well for the datasets analyzed. Artificial censoring scenarios were used in a Monte Carlo simulation analysis to show that the fitted trends were unbiased and the approximate p‐values were accurate for as few as 10 uncensored concentrations during a three‐year period, assuming a sampling frequency of 15 samples per year. Trend estimates for the full model were compared with a model without the streamflow anomaly and a model in which the seasonality was modeled using standard trigonometric functions, rather than seasonal application rates. Exclusion of the streamflow anomaly resulted in substantial increases in the mean‐squared error and decreases in power for detecting trends. Incorrectly modeling the seasonal structure of the concentration data resulted in substantial estimation bias and moderate increases in mean‐squared error and decreases in power.     

STATISTICAL ANALYSIS OF THE IMPACT OF GROUND WATER PUMPAGE ON LOW-FLOW HYDROLOGY1

ABSTRACT: Ground-water pumpage withdrew 57 cubic feet per second from aquifers beneath the Yahara River Basin in 1970. Forty-six cubic feet per second were exported by the diversion of treated wastewater from the drainage basin. The low-flow hydrology of the upper Yahara River has been impacted by this diversion. Prior to 1959, the wastewater was discharged into the river, augmenting the baseflow during low-flow periods. As much as 85% of streamflow was due to effluent discharge. In 1959 the wastewater was transferred from the river basin. The result was a decrease of about one-third in mean annual streamflow, and a decrease of more than 50% in the 7Q₂ and 7Q₁₀. Regression analysis showed the annual 7-day low-flow and 60-day low-flow have a statistically significant correlation with mean annual flow. Using predictions of future mean annual discharge of the river with increasing interbasin transfers, it is shown that by 1990 there is a significant probability that in some years the 60-day low-flow in the river will be zero.     

Daily Updating of Operational Statistical Seasonal Water Supply Forecasts for the western U.S.1

Abstract: Official seasonal water supply outlooks for the western United States are typically produced once per month from January through June. The Natural Resources Conservation Service has developed a new outlook product that allows the automated production and delivery of this type of forecast year‐round and with a daily update frequency. Daily snow water equivalent and water year‐to‐date precipitation data from multiple SNOTEL stations are combined using a statistical forecasting technique (“Z‐Score Regression”) to predict seasonal streamflow volume. The skill of these forecasts vs. lead‐time is comparable to the official published outlooks. The new product matches the intra‐monthly trends in the official forecasts until the target period is partly in the past, when the official forecasts begin to use information about observed streamflows to date. Geographically, the patterns of skill also match the official outlooks, with highest skill in Idaho and southern Colorado and lowest skill in the Colorado Front Range, eastern New Mexico, and eastern Montana. The direct and frequent delivery of objective guidance to users is a significant new development in the operational hydrologic seasonal forecasting community.     

EVALUATION OF NITRATE DATA IN THE OCKLAWAHA RIVER BASIN,FLORIDA (1953–2002)1

ABSTRACT: Nitrate levels in the Ocklawaha River Basin in north central Florida were reviewed over a 50‐year period. Data were obtained from the literature, U.S. Environmental Protection Agency (USEPA) STOrage and RETrieval (STORET), and U.S. Geological Survey (USGS) databases. The study objective was to determine whether nitrate concentrations are increasing and if so, whether this increase is linked to land use changes. Increasing nitrate levels were seen at 5 of the 14 stations, while other stations showed no trend or a decreasing trend. Median nitrate concentrations in the Ocklawaha River increased from 0.07 mg‐N/L to 0.78 mg‐N/L at sites downstream from the Silver River. Throughout the Rodman Reservoir, median nitrate concentrations decreased from 0.48 mg‐N/L to 0.01 mg‐N/L and increased to 0.04 mg‐N/L after the Kirkpatrick Dam. Flow and concentration relationships were correlated for five stations. At four of the five stations nitrate concentrations decreased in response to increasing flow, likely the result of dilution with nitrate poor water. Changes in land use over a 20‐ year period (1970 to 1990) also were monitored. Sources of nitrate have been linked by isotopic analysis to organic and inorganic fertilizers, which appear to be related to increased urbanization and an increase in lawns that require nutrient fertilization.     

HYDROLOGICAL MODELING OF THE IROQUOIS RIVER WATERSHED USING HSPF AND SWAT1

ABSTRACT: The performance of two popular watershed scale simulation models — HSPF and SWAT — were evaluated for simulating the hydrology of the 5,568 km² Iroquois River watershed in Illinois and Indiana. This large, tile drained agricultural watershed provides distinctly different conditions for model comparison in contrast to previous studies. Both models were calibrated for a nine‐year period (1987 through 1995) and verified using an independent 15‐year period (1972 through 1986) by comparing simulated and observed daily, monthly, and annual streamflow. The characteristics of simulated flows from both models are mostly similar to each other and to observed flows, particularly for the calibration results. SWAT predicts flows slightly better than HSPF for the verification period, with the primary advantage being better simulation of low flows. A noticeable difference in the models' hydrologic simulation relates to the estimation of potential evapotranspiration (PET). Comparatively low PET values provided as input to HSPF from the BASINS 3.0 database may be a factor in HSPF's overestimation of low flows. Another factor affecting baseflow simulation is the presence of tile drains in the watershed. HSPF parameters can be adjusted to indirectly account for the faster subsurface flow associated with tile drains, but there is no specific tile drainage component in HSPF as there is in SWAT. Continued comparative studies such as this, under a variety of hydrologic conditions and watershed scales, provide needed guidance to potential users in model selection and application.     

Pre-instrumental perspectives on Arkansas River cross-watershed flow variability

We present four reconstruction estimates of Arkansas River baseflow and streamflow using a total of 78 tree-ring chronologies for three streamflow gages, geographically spanning the headwaters in Colorado to near the confluence of the Arkansas-Mississippi rivers. The estimates represent different seasonal windows, which are dictated by the shared limiting forcing of precipitation on seasonal tree growth and soil moisture—and subsequently on the variability of Arkansas River discharge. Flow extremes that were higher and lower than what has been observed in the instrumental era are recorded in each of the four reconstructions. Years of concurrent, cross-basin (all sites) low flow appear more frequently during the 20th and 21st Centuries compared to any period since 1600 A.D., however, no significant trend in cross-basin low flow is observed. As the most downstream major tributary of the Mississippi River, the Arkansas River directly influences flood risk in the Lower Mississippi River Valley. Estimates of extreme high flow in downstream reconstructions coincide with specific years of historic flooding documented in New Orleans, Louisiana, just upstream of the Mississippi River Delta. By deduction, Mississippi River flooding in years of low Arkansas River flow imply exceptional flooding contributions from the Upper Mississippi River catchments.     

Groundwater Level Trends and Drivers in Two Northern New England Glacial Aquifers

We evaluated long‐term trends and predictors of groundwater levels by month from two well‐studied northern New England forested headwater glacial aquifers: Sleepers River, Vermont, 44 wells, 1992‐2013; and Hubbard Brook, New Hampshire, 15 wells, 1979‐2004. Based on Kendall Tau tests with Sen slope determination, a surprising number of well‐month combinations had negative trends (decreasing water levels) over the respective periods. Sleepers River had slightly more positive than negative trends overall, but among the significant trends (p < 0.1), negative trends dominated 67 to 40. At Hubbard Brook, negative trends outnumbered positive trends by a nearly 2:1 margin and all seven of the significant trends were negative. The negative trends occurred despite generally increasing trends in monthly and annual precipitation. This counterintuitive pattern may be a result of increased precipitation intensity causing higher runoff at the expense of recharge, such that evapotranspiration demand draws down groundwater storage. We evaluated predictors of month‐end water levels by multiple regression of 18 variables related to climate, streamflow, snowpack, and prior month water level. Monthly flow and prior month water level were the two strongest predictors for most months at both sites. The predictive power and ready availability of streamflow data can be exploited as a proxy to extend limited groundwater level records over longer time periods.     

Observed Changes in Climate and Streamflow in the Upper Rio Grande Basin

Observed streamflow and climate data are used to test the hypothesis that climate change is already affecting Rio Grande streamflow volume derived from snowmelt runoff in ways consistent with model‐based projections of 21st‐Century streamflow. Annual and monthly changes in streamflow volume and surface climate variables on the Upper Rio Grande, near its headwaters in southern Colorado, are assessed for water years 1958–2015. Results indicate winter and spring season temperatures in the basin have increased significantly, April 1 snow water equivalent (SWE) has decreased by approximately 25%, and streamflow has declined slightly in the April–July snowmelt runoff season. Small increases in precipitation have reduced the impact of declining snowpack on trends in streamflow. Changes in the snowpack–runoff relationship are noticeable in hydrographs of mean monthly streamflow, but are most apparent in the changing ratios of precipitation (rain + snow, and SWE) to streamflow and in the declining fraction of runoff attributable to snowpack or winter precipitation. The observed changes provide observational confirmation for model projections of decreasing runoff attributable to snowpack, and demonstrate the decreasing utility of snowpack for predicting subsequent streamflow on a seasonal basis in the Upper Rio Grande Basin.     

AUTOMATED METHODS FOR ESTIMATING BASEFLOW AND GROUND WATER RECHARGE FROM STREAMFLOW RECORDS1

ABSTRACT: To quantify and model the natural ground water recharge process, six sites located in the midwest and eastern United States where previous water balance observations had been made were compared to computerized techniques to estimate: (1) base flow and (2) ground water recharge. Results from an existing automated digital filter technique for separating baseflow from daily streamflow records were compared to baseflow estimates made in the six water balance studies. Previous validation of automated baseflow separation techniques consisted only of comparisons with manual techniques. In this study, the automated digital filter technique was found to compare well with measured field estimates yielding a monthly coefficient of determination of 0.86. The recharge algorithm developed in this study is an automated derivation of the Rorabaugh hydrograph recession curve displacement method that utilizes daily streamflow. Comparison of annual recharge from field water balance measurements to those computed with the automated recession curve displacement method had coefficients of determination of 0.76 and predictive efficiencies of 71 percent. Monthly estimates showed more variation and are not advocated for use with this method. These techniques appear to be fast, reproducible methods for estimating baseflow and annual recharge and should be useful in regional modeling efforts and as a quick check on mass balance techniques for shallow water table aquifers.     

NITRATE CONCENTRATIONS IN KARST SPRINGS IN AN EXTENSWELY GRAZED AREA1

ABSTRACT: The impact on water quality by agricultural activity in karst terrain is an important consideration for resource management within the Appalachian Region. Karst areas comprise about 18 percent of the Region's land area. An estimated one-third of the Region's farms, cattle, and agricultural market value are located on karst terrain. Nitrate concentrations were measured in several karst springs in Southeastern West Virginia in order to determine the impact of animal agriculture on nitrate pollution of the karst ground water system. Karst basins with 79, 51, 16, and 0 percent agriculture had mean nitrate concentrations of 15.8, 12.2, 2.7, and 0.4 mg/l, respectively. A strong linear relationship between nitrate concentration and percent agricultural land was shown. Median nitrate concentration increased about 0.19 mg l^-1 per percent increase in agricultural land. Weather patterns were also found to significantly affect the median nitrate concentrations and the temporal variability of those concentrations. Lower nitrate concentrations and lower temporal variability were observed during a severe drought period. It was concluded that agriculture was significantly affecting nitrate concentrations in the karst aquifer. Best management practices may be one way to protect the ground water resource.